BIG.art: Using Machine Learning to Create High-Res Fine Art

How to use GLIDE and BSRGAN to create ultra-high-resolution digital paintings with fine details

Sample Results from BIG.art, Images by Author

I have been experimenting and writing about using AI/ML to create art from text descriptions for over a year now. During this time, I have noticed a significant increase in interest in this area, in part due to the burgeoning NFT art market.

After looking at dozens of ML models for generating art, the best one I have seen so far is GLIDE from OpenAI [1]. Coupled with a super-resolution resize model called BSRGAN from ETH in Zurich [2], I find the results to be excellent.

For example, below are the results from two of my earlier projects, MAGnet using CLIP+SWAGAN and GANshare One using CLIP+VQGAN, compared to results from the new system on the right. The prompts I used were “a painting of rolling farmland,” “an abstract painting with orange triangles,” and “a still life painting of a bowl of fruit.”